Update app.py

app.py

@@ -1,62 +1,76 @@
 import os
 import tempfile
+import shutil
 import gradio as gr
 import tensorflow as tf
 from tensorflow.python.ops.numpy_ops import np_config
 
-# -------------------------
-# TensorFlow configuration
-# -------------------------
+# -----------------------------
+# TensorFlow setup
+# -----------------------------
+# Enable eager execution & NumPy behavior
 tf.config.run_functions_eagerly(True)
 np_config.enable_numpy_behavior()
 
-# -------------------------
+# -----------------------------
 # Install Spleeter if missing
-# -------------------------
-if not os.path.exists("/home/user/.spleeter_installed"):
-    import install_spleeter  # assumes install_spleeter.py is available
-    open("/home/user/.spleeter_installed", "w").close()
+# -----------------------------
+SPLEETER_FLAG = "/home/user/.spleeter_installed"
+if not os.path.exists(SPLEETER_FLAG):
+    os.system("pip install tensorflow==2.12 spleeter==2.3.2")
+    open(SPLEETER_FLAG, "w").close()
 
 from spleeter.separator import Separator
 
-# -------------------------
+# -----------------------------
 # Initialize separator
-# -------------------------
-separator = Separator("spleeter:2stems", multiprocess=False)
+# -----------------------------
+# 2 stems: vocals + accompaniment
+separator = Separator("spleeter:2stems")
 
-# -------------------------
+# -----------------------------
 # Audio separation function
-# -------------------------
+# -----------------------------
 def separate_audio(audio_file):
-    """
-    Takes an audio file path, separates vocals & accompaniment,
-    and returns paths to the resulting WAV files.
-    """
+    # Create temporary directory for output
     tmp_dir = tempfile.mkdtemp()
     
-    # Use Spleeter's file-based separation
-    separator.separate_to_file(audio_file, tmp_dir, codec="wav")
-    
-    base_name = os.path.splitext(os.path.basename(audio_file))[0]
-    vocals_path = os.path.join(tmp_dir, base_name, "vocals.wav")
-    instr_path = os.path.join(tmp_dir, base_name, "accompaniment.wav")
-    
-    return vocals_path, instr_path
+    try:
+        # Spleeter works best with file paths, not waveform arrays
+        separator.separate_to_file(audio_file, tmp_dir, codec="wav")
+        
+        # Grab separated file paths
+        vocals_path = os.path.join(tmp_dir, os.path.basename(audio_file).replace(".wav", ""), "vocals.wav")
+        accompaniment_path = os.path.join(tmp_dir, os.path.basename(audio_file).replace(".wav", ""), "accompaniment.wav")
+        
+        # Return file paths
+        return vocals_path, accompaniment_path
+    except Exception as e:
+        return str(e), None
+    finally:
+        # Note: We do NOT delete tmp_dir immediately, Gradio needs file paths
+        pass
 
-# -------------------------
+# -----------------------------
 # Gradio UI
-# -------------------------
+# -----------------------------
 with gr.Blocks() as iface:
-    gr.Markdown("## Audio Source Separation (Vocals & Instrumentals)")
+    gr.Markdown("## Audio Separator (Vocals + Accompaniment)")
     
-    audio_input = gr.Audio(label="Upload Audio", type="filepath")
-    vocals_output = gr.Audio(label="Vocals", type="filepath")
-    instr_output = gr.Audio(label="Instrumental", type="filepath")
+    audio_input = gr.Audio(label="Upload WAV/MP3 file", type="filepath")
+    output_vocals = gr.Audio(label="Vocals")
+    output_acc = gr.Audio(label="Accompaniment")
     
     separate_btn = gr.Button("Separate Audio")
-    separate_btn.click(separate_audio, inputs=audio_input, outputs=[vocals_output, instr_output])
+    
+    separate_btn.click(
+        fn=separate_audio,
+        inputs=audio_input,
+        outputs=[output_vocals, output_acc]
+    )
 
-# -------------------------
-# Launch Gradio app
-# -------------------------
-iface.launch(server_name="0.0.0.0", server_port=7860, share=False)
+# -----------------------------
+# Launch app
+# -----------------------------
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=7860)